certain devices for cracks, rust, etc. Some of these issues are difficult to identify for a human and your company has seen increasing customer complaints – the customer has paid for an inspection and the field agent said there was no problem, but it later turned out there actually was. The team has come up with a proposal to engage AI to identify issues.
On evaluating the existing system, it is seen that the mobile phone network connection is not good or consistent .
What solution can work for them?
A . Use AutoML Vision Edge models.
B . Use the Rust programming language instead of Python to identify issues like rust.
C . Use Cloud TPUs which will be able to do the analysis faster on the cloud. Thus re-sponses also will be fast.
D . Use TensorFlow to create custom models and deploy it as TensorFlow Lite mod-els.
Answer: A
Explanation:
AutoML Vision Edge model can be deployed to one of several types of edge devices, such as mobile phones, ARM-based devices, and the Coral Edge TPU https://cloud.google.com/vision/automl/docs/edge-quickstart
Latest Cloud-Digital-Leader Dumps Valid Version with 40 Q&As
Latest And Valid Q&A | Instant Download | Once Fail, Full Refund